融合启发式搜索的改进极快决策树算法在多规格货物智能混合装载中的应用

针对多规格货物装载效率较低问题,提出了一种融合启发式搜索的改进极快决策树智能装箱算法,该算法首先计算并择优选取样本信息熵,然后构建生成货物装箱决策树模型,最后基于启发式搜索方法对货物装载后的剩余空间进行合并再利用。通过保证决策树每个节点装入货物体积最大,对待装货物进行快速决策。最后,基于七组异构性逐渐增强的货物数据对算法进行仿真实验,结果表明：本算法在保证较高集装箱利用率的情况下实现了快速装箱。

Study on Intelligent Mixed Loading of Multi-specification Cargo Based on EFDT-HS Algorithm

Concerning the problem that the cargo low efficiency problem of many specifications, this paper proposed a fusion of heuristic search to improve fast packing and intelligent decision tree algorithm.Firstly, selected the sample information for calculation and optimal entropy to ensure maximum volume into the container.Secondly,built the decision tree model for produces goods.Then,based on heuristic search to merge the remaining space to load the new space after loading the goods.By ensuring that each node of the decision tree loads the largest volume of goods, quick decisions are made on loaded goods.Lastly,The algorithm is simulated based on seven groups of cargo data with increasing heterogeneity, The simulation experimental results show that the algorithm can realize fast loading while ensuring a higher utilization rate of containers.